Many scientific, engineering, medical, and other technologies seek to identify the presence of an object within a medium. For example, some technologies detect the presence of buried landmines in a roadway or a field for military or humanitarian purposes. Such technologies may use ultra wideband ground-penetrating radar (“GPR”) antennas that are mounted on the front of a vehicle that travels on the roadway or across the field. The antennas are directed into the ground with the soil being the medium and the top of the soil or pavement being the surface. GPR systems can be used to detect not only metallic objects but also non-metallic objects whose dielectric properties are sufficiently different from those of the soil. When a radar signal strikes a subsurface object, it is reflected back as a return signal to a receiver. Current GPR systems typically analyze the strength or amplitude of the return signals directly to identify the presence of the object. Some GPR systems may, however, generate tomography images from the return signals. In the medical field, computer-assisted tomography uses X-rays to generate tomography images for detecting the presence of abnormalities (i.e., subsurface objects) within a body. In the engineering field, GPR systems have been designed to generate spatial images of the interior of concrete structures such as bridges, dams, and containment vessels to assist in assessing the integrity of the structures. In such images, the subsurface objects represented by such images tend to appear as distinct bright spots. In addition to referring to a foreign object that is within a medium, the term “object” also refers to any characteristic of the medium (e.g., crack in the medium and change in medium density) that is to be detected.
Using current imaging techniques, computational systems attached to arrays that contain dozens of antennas are unable to produce radar tomography images of the subsurface in real time. A real-time system needs to process the return signals from successive sampling locations of the vehicle as it travels so that, in the steady state, the return signals for one sampling location are processed within the time between samplings. Moreover, in the case of a vehicle that detects landmines, a real-time system may need to detect the presence of the landmine in time to stop the vehicle from hitting the landmine.
Some current technologies seek to detect the presence of new objects that were not detected in previous passes. For example, a convoy of military vehicles may travel over a certain roadway fairly often. If access to the roadway is not tightly controlled, the military may need to check, each time a convoy is to travel down the roadway, for the presence of landmines or other objects that may pose a hazard to the convoy. As another example, a civil engineering firm may check bridges, dams, and other structures on a regular basis (e.g., yearly) for the presence of new subsurface defects (e.g., cracks). Each time the structure, roadway, or area is scanned, large amounts of data may be collected and processed. For example, the scan of the roadway may collect GPR return signals every few centimeters. GPR systems may generate image frames from the return signals and detect subsurface objects in those image frames. When these GPR systems have access to data from previous scans of that structure or roadway, the GPR systems may detect change by comparing (i) images reconstructed along the latest scan to images reconstructed along previous scans, or (ii) newly detected objects to previously detected objects.
Current GPR systems do not use results from previous scans to perform change detection for objects in real time. A major hurdle in achieving this goal is that the cost of storing the vast amounts of data collected from previous scans and comparing data from those previous scans to the latest scan may be prohibitive. A real-time system needs to process the return signals from successive sampling locations of the vehicle down-track so that, in the steady state, the return signals for one sampling location are processed within the time between samplings. Moreover, in the case of a vehicle that detects landmines, a real-time system may need to detect the presence of the landmine in time to stop the vehicle that is collecting the return signals before it hits the landmine.
Current GPR systems may use several transmitter and receiver antenna pairs that are typically oriented in the same direction. For example, an array of transmitter and receiver pairs may be mounted in a linear array on a vehicle with the antennas oriented across the roadway, that is, perpendicular to the direction of the roadway. Transmitters oriented across the roadway emit a signal that is polarized across the roadway. The return signals from such transmitters are strongest when a subsurface object has a significant extent across the roadway. For example, an object that extends across one-quarter of the roadway will produce a return signal that is much stronger than an object that extends only a very short distance across the roadway. Thus, a large boulder or a pipeline crossing the roadway will produce a strong return signal, but a pipeline that extends in the direction of the roadway will produce a much weaker return signal. As a result, such GPR systems may produce results that are less than desirable for objects (e.g., cracks or pipelines) with a short extent across the roadway. Although some GPR systems use antenna arrays with transmitters and receivers with different orientations, these systems do not effectively detect subsurface objects in real time.